Image created with Gemini. Image prompt: A 1983 Russell Mulcahy music video still in 16:9, a colossal glowing carved jade imperial seal ringed with Chinese cloud motifs hangs above a sweeping marble staircase in a vast fog-filled Victorian Gothic academy at night, a black disc eclipses the seal leaving a molten gold corona, an anonymous woman in a wind-blown luminous white dress reaches up from the staircase base as adult male robed scholar apparitions with faintly glowing eyes ascend through billowing smoke and slow-motion doves, blinding white backlight through arched doorways, deep blue-black shadows, 35mm film grain with heavy bloom and halation, the words ZHIPU AI emblazoned across the top in huge bold chrome serif movie-title lettering with glowing backlight, no other text.
// The Harness Effect // (bookmark it) Now more that ever pay very close attention to the orchestration harness and its effect on costs and performance. This study ran 22 evaluation tasks on six foundation models (Claude Sonnet 4.6, Gemini 3.1, Qwen 3.6, GLM 5.1, and others),”
https://x.com/dair_ai/status/2075241322655727682
I’m the kind of man who can confidently pass a blind test between Coke, Pepsi, and Diet Coke. But if I’m brutally honest, I probably can’t pass a blind test between GPT-5.6 Sol, Claude Fable 5, and GLM-5.2 for 95% of my daily use cases.”
https://x.com/Yuchenj_UW/status/2074903450782257336
This is consistent with our experience. GLM 5.2 is the best open-weight model. Frontier commercial models are better. GLM 5.2 can be brought up to ~Opus 4.7 level with the appropriate harness infrastructure on a diverse task set, and in particular, on systems+software eng.”
https://x.com/mbusigin/status/2074238100251799998
I cannot believe how good GLM 5.2 is. Several weeks in now and it’s mostly all I have been using. It doesn’t have the alignment issue of cloud AI, it’s much more clear what it can do and can’t because it doesn’t care about you taking another $$$ spin at the token slot machine.”
https://x.com/__tinygrad__/status/2074206866641752190
We’re introducing Provisioned Throughput: reserved inference capacity for frontier open models, with token-based pricing and a 99% uptime SLA. Serverless simplicity, guaranteed capacity, up to 90% lower cost vs. Opus 4.8. Get started with MiniMax M3 + GLM-5.2, read more 🧵”
https://x.com/togethercompute/status/2074756085785722930
GLM-5.2 is close to Opus Grok 4.5 allegedly beats Opus and gpt-5.5 Meta even has something that’s supposedly close to gpt-5.5 Feels like it barely matters now”
https://x.com/theo/status/2074931078104805668
At Databricks, we built an internal coding benchmark on our multi-million-line codebase. Biggest takeaways: 1. Open-source coding models are no longer toys. GLM-5.2 is strong and cheaper. 2. OpenAI, Anthropic, and GLM-5.2 are all on the Pareto frontier. The real unlock is an”
https://x.com/Yuchenj_UW/status/2074956726940680558
Big news: Grok-4.5 has landed #3 in the Code Arena: Frontend. – On par with GLM-5.2 (Max) and Claude Opus 4.8 (Thinking) – Significant improvement over Grok-4.3 (#62 -> #3) – #2 for Content Creation Tools, Simulations, Gaming and Reference-Based Design – #3 for Consumer Product”
https://x.com/arena/status/2075301317560742373
https://t.co/k6Bcz1C0NT’s GLM-5.2 scores an estimated 152 on the Epoch Capabilities Index, the highest of any open-weight model we’ve evaluated. It remains behind models like Gemini 3 Pro, released over 7 months ago.”
https://x.com/EpochAIResearch/status/2074894535558300103
Added Grok 4.5 to my Surface Evolver benchmark. It’s on the frontier, achieving a better pass rate than kimi/glm at a similar price point.”
https://x.com/Deep_Burner/status/2074958078227951813
If these scores are real, Tencent has just become one of the leaders of open source. Hy3 is a 295B 21AB model that at least beats GLM 5.1 in blind tests. Might even warrant architecture transition (it’s a basic GQA). Good job.”
https://x.com/teortaxesTex/status/2074012467886178725
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